Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Electrical and electronic engineering, 3. MEDICAL AND HEALTH SCIENCES
Diagnosis and monitoring of Parkinson's disease has a number of challenges as there is no definitive biomarker despite the broad range of symptoms. Research is ongoing to produce objective measures that can either diagnose Parkinson's or act as an objective decision support tool. Recent research on speech based measures have demonstrated promising results. This study aims to investigate the characteristics of the glottal source signal in Parkinsonian speech. An experiment is conducted in which a selection of glottal parameters are tested for their ability to discriminate between healthy and Parkinsonian speech. Results for each glottal parameter are presented for a database of 50 healthy speakers and a database of 16 speakers with Parkinsonian speech symptoms. Receiver operating characteristic (ROC) curves were employed to analyse the results and the area under the ROC curve (AUC) values were used to quantify the performance of each glottal parameter. The results indicate that glottal parameters can be used to discriminate between healthy and Parkinsonian speech, although results varied for each parameter tested. For the task of separating healthy and Parkinsonian speech, 2 out of the 7 glottal parameters tested produced AUC values of over 0.9.
Hanratty J, Deegan C, Walsh M, Kirkpatrick B. Analysis of glottal source parameters in Parkinsonian speech. Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:3666-3669. doi: 10.1109/EMBC.2016.7591523. PMID: 28269089.
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This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.